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| Emergency Decision-Making of Production Safety Accidents by Integrating Event Knowledge Graphs and Case-Based Reasoning |
| Guo Yu1,2, Liu Fangyu1, Li Changfei1, Zhang Haitao1,2 |
1.School of Business and Management, Jilin University, Changchun 130015
2.The Information Resource Research Center, Jilin University, Changchun 130015 |
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Abstract To improve the accuracy and intelligence of emergency decision-making for production safety accidents, this paper proposes an emergency decision-making method that integrates event knowledge graphs and case-based reasoning. This method addresses the entire process after an accident, including “element extraction, case matching, evolution reasoning, decision generation, and effect evaluation”. First, an event knowledge graph for production safety accidents is constructed based on multimodal data such as text, images, and videos. Through multimodal event extraction and relation recognition, the key entities, causal chains, and evolutionary logic of accidents are characterized, and a structured representation of accident knowledge is realized. Second, a case-based reasoning mechanism is introduced, and a case representation and retrieval method based on the event graph is designed. The path reasoning is used to identify high-confidence tasks and risk entities to realize the migration mapping from the historical disposal chains to the target accident situation and generate operable emergency decision-making suggestions. Finally, an empirical study is conducted for a typical emergency scenario of fire accidents, constructing source and target case bases to verify the effectiveness of case retrieval and consistency of decision generation. The unsupervised simple contrastive learning of sentence embeddings semantic consistency evaluation method is used for a quantitative comparison between the predicted and actual disposal schemes. The results indicate that the proposed method can effectively match similar cases and infer disposal tasks under conditions of incomplete information. In addition, the generated key decision recommendations encompassing command and dispatch, on-site control and risk isolation, casualty rescue, and personnel transfer are highly consistent with the actual disposal measures of the target cases. This study provides methodological support for rapid assessment, solution recommendations, and collaborative decision-making in emergency responses to production safety accidents.
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Received: 29 August 2025
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